Toward Atomic Resolution of Membranes and Membrane-Associated Machines

膜和膜相关机器的原子分辨率

• 批准号: 8572065
• 负责人: Adam Frost
• 金额: $ 46.96万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-30 至 2015-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8572065
• 关键词: Algorithms; Animal Model; Binding; Binding Proteins; Biochemical; Biological Assay; Cell division; Cell physiology; Cells; Cellular Membrane; Chromosome Mapping; Communication; Complex; Cryoelectron Microscopy; Disease; Electrons; Genetic; Genome; Goals; Image Analysis; In Vitro; Laboratories; Learning; Lipids; Membrane; Methods; Modeling; Molecular; Pathway interactions; Research; Resolution; Shapes; Signal Transduction; Site; Structural Models; Structure; Technology; Translating; detector; electron optics; in vivo; innovation; loss of function; membrane model; migration; novel; pathogen; programs; reconstitution; reconstruction; tool

DESCRIPTION (provided by applicant): The unifying goal of this proposal is to understand the structures and functions of machines that assemble on cellular membranes. Cells depend upon these machines in order to transform the shape, size and connectivity of their membranes and such "remodeling" underlies cell division, migration, differentiation, and communication. In addition, every pathogen hijacks or disrupts membrane-associated complexes to infect or escape from cells. Despite such central importance we lack comprehensive models of how membrane-binding proteins transduce signals, oligomerize, or remodel the size, shape and topology of cellular membranes. To overcome the intrinsic challenges in studying multi-component complexes that assemble transiently on membranes, we will develop genetic, biochemical and structural methods to discover and characterize bilayer-bound machines in molecular detail and to learn how they function within intricate cellular pathways. We build genome-scale maps of genetic interaction networks in model organisms to identify multi-component complexes and to infer their functions. We develop methods for reconstituting membrane-binding proteins in the presence of model membranes that mimic the in vivo target membrane in topology, lipid composition, size, and shape. We then leverage advances in cryo-electron microscopy (cryoEM) with our novel image analysis algorithms to solve structures of these machines in their native, membrane-associated states. These innovative tools are distinct methodologically but reinforcing: our genetic maps first define complexes for in depth in vitro study; and after reconstitute and solve 3D reconstructions by cryoEM we probe the functional predictions of our models with loss-of-function versus second-site suppression assays in vivo. These orthogonal approaches thus provide synergistic evidence for the mechanisms that drive cellular functions and result in genuine atomic-resolution understanding of the structures and functions we study. In concert with technology advances in electron optics and electron detectors, my laboratory is overcoming the genetic, biochemical and computational challenges responsible for the lack of structural models for membrane-bound protein assemblies. The aims outlined here are first, critical steps in our long-term research program to determine how the mechanisms we discover are corrupted by disease or hijacked by pathogens. Our ultimate objective is to translate this understanding into effective and tolerable treatments for diseases caused by defective or co-opted membrane-associated machines.

描述（由申请人提供）：本提案的统一目标是了解组装在细胞膜上的机器的结构和功能。细胞依赖于这些机器来改变其膜的形状，大小和连接性，这种“重塑”是细胞分裂，迁移，分化和通讯的基础。此外，每种病原体都会劫持或破坏膜相关复合物，以感染或逃离细胞。尽管如此重要，我们缺乏全面的模型，膜结合蛋白如何传递信号，寡聚化，或重塑细胞膜的大小，形状和拓扑结构。 为了克服研究在膜上瞬时组装的多组分复合物的内在挑战，我们将开发遗传，生物化学和结构方法来发现和表征分子细节中的双层结合机器，并了解它们如何在复杂的细胞通路中发挥作用。我们在模式生物中构建基因组规模的遗传相互作用网络图，以识别多组分复合物并推断其功能。我们开发了在模型膜存在下重建膜结合蛋白的方法，该模型膜在拓扑结构、脂质组成、大小和形状上模仿体内靶膜。然后，我们利用低温电子显微镜（cryoEM）的进步与我们的新的图像分析算法来解决这些机器在其原生的膜相关状态的结构。这些创新的工具在方法上是不同的，但加强：我们的遗传图谱首先定义复杂的深入体外研究;并通过cryoEM重建和解决三维重建后，我们探测我们的模型的功能预测与功能丧失与第二个网站抑制测定体内。因此，这些正交方法为驱动细胞功能的机制提供了协同证据，并导致我们研究的结构和功能的真正原子分辨率的理解。 与电子光学和电子探测器的技术进步相一致，我的实验室正在克服遗传，生物化学和计算方面的挑战，这些挑战导致缺乏膜结合蛋白质组装的结构模型。这里概述的目标是我们长期研究计划的第一个关键步骤，以确定我们发现的机制如何被疾病破坏或被病原体劫持。我们的最终目标是将这种理解转化为有效和可耐受的治疗方法，用于治疗由缺陷或增选的膜相关机器引起的疾病。